Abstract:

To visualize vibrations in mechanical systems, e.g., machine tools, their
movements are measured by means of suitable sensors. The signals from these sensors
are processed and displayed as animated pictures on a computer screen.
Accelerometers have been chosen as the most suitable sensors for this purpose.
Their main advantages include small size, wide sensitivity range and frequency
bandwidth. In addition, accelerometers measure signals with reference to the Earth, so
they do not require stable fixtures such as used with cameras or lasers.
The visualization methodology involves nine accelerometers attached to a
mechanical component, e.g., a dynamometer's platform. Vibration signals were acquired
using a data acquisition (DAQ) system which is controlled by a LabVIEW®-based
program. These signals are processed to suppress errors and convert acceleration into
generalized coordinate that describes motion of the visualized component as a rigid
plate's movement in 3-D space.
The animation is accomplished by displaying a time series of pictures representing
instantaneous position of the plate. The animation program employs homogenous
coordinate transformation to draw 3-D 'wireframe' pictures. Since various errors distort
the measured signals, the animated movement may be inaccurate. The knowledge of a
mathematical model of the system whose vibrations are animated allows detection and
suppression of distortions. For this purpose, the signals measured from the actual
dynamic system are compared with the signals simulated by the system's model subjected
to the same excitation as the actual system. Discrepancies between the actual and
simulated signals are detected. They are analyzed to identify possible sources and forms
of distorting signals. As the next step, the measured (actual) signals are corrected by
removing estimated distortions.
A methodology and software package capable of performing all functions
necessary to implement the visualization of vibration have been developed in this
research using LabVIEW® programming environment. As compared with commercial
software for experimental modal analysis, the most distinctive feature of the developed
package is improved accuracy achieved by applying concepts utilized in control theory,
such as modeling of multi-input-multi-output (MIMO) systems and on-line system
identification for the model development and correction of signals.